1. Field of the Invention
The present invention relates to an image processing apparatus and method and, more particularly, to an image processing apparatus and method of adjusting the hue of an input image signal.
The present invention also relates to an image reproducing method and apparatus and, more particularly, to an image reproducing method and apparatus for converting an image sensing signal obtained from an image sensing device, such as an image sensing tube or a CCD, into a visualizable image signal, e.g., an NTSC-RGB signal.
2. Description of the Related Art
In a television camera using an image sensing device such as a CCD, some image reproduction parameters are generally determined from image sensing data during image reproduction processing, in order to constantly obtain images which apparently give the same impression or to obtain as faithful reproduced images as possible regardless of deterioration with time of the image sensing device or a color filter and changes in an illuminating light source. The image sensing data is two-dimensional digital image data formed from an image signal obtained by photographing an object by using an image sensing device.
Examples of the image reproduction parameters are a color temperature and a reproduction luminance level. The image production parameters are used to correct the color temperature or set the reproduction luminance level.
More specifically, the correction of the color temperature is to adjust a so-called white balance so that an object which is supposed to look white looks white. Generally, this color temperature correction is performed on the basis of image sensing data. That is, data of an object which is supposed to look white is extracted from image sensing data, and a white balance coefficient as one image reproduction parameter is determined on the basis of the extracted data. In the white balance adjustment, a plurality of color component signals constituting an output image signal from an image sensing device are amplified in accordance with the white balance coefficient. Consequently, the signal levels of the color components constituting the image signal of the object which is supposed to look white are so adjusted as to be equal to each other.
The setting of the reproduction luminance level is done by calculating a luminance distribution from image sensing data and setting an optimum reproduction luminance level (range). The parameter is adjusted such that a reproduced image is obtained within this range, and the image is reproduced.
FIGS. 1 and 2 are block diagrams showing configurations for performing the color temperature correction.
Referring to FIG. 1, complementary color data (consisting of color component signals of magenta Ma, green Gr, Yellow Ye, and cyan Cy) obtained by an image sensing unit 1 is supplied to a complementary color-pure color converting unit 11. The complementary color data is converted into pure color data (consisting of color component signals of red R, green G, and blue B) in the converting unit 11. The white balance of the pure color data obtained by the complementary color-pure color converting unit 11 is adjusted by a white balance (WB) adjusting unit 12 in the subsequent stage, and the gamma of the data is corrected by a gamma correcting unit 4.
In the configuration shown in FIG. 1 as above, the WB adjusting unit 12 is arranged subsequently to the complementary color-pure color converting unit 11, and the color temperature correction is done by performing the white balance adjustment for the pure color data (R,G,B) after complementary colors are converted into pure colors. This configuration is advantageous in that the color temperature correction can be relatively easily performed because the gain of the pure color data (R,G,B) can be directly adjusted.
In the configuration shown in FIG. 2, on the other hand, a WB adjusting unit 2 adjusts the white balance of complementary color data (Ma,Gr,Ye,Cy) obtained by an image sensing unit 1. Thereafter, a complementary color-pure color converting unit 3 performs complementary color-pure color conversion to obtain pure color data (R,G,B). This configuration has the advantage that a luminance signal with a higher resolution than that obtained in the configuration shown in FIG. 1 can be easily obtained.
The method of adjusting the hue of an image by adjusting the white balance is effective when many objects which are supposed to look white exist in an image signal obtained from an image sensing device. However, no such object which is supposed to look white exists in an image signal or only a very few such objects exist in an image signal in specific instances. In these instances, therefore, it is in principle impossible to adjust the hue by adjusting the white balance. In such instances, the general approach is to average image sensing data of one image plane for each color component and adjust the white balance by using the average. However, a color indicated by the obtained average is not necessarily white (the color of a light source), and so the white balance cannot be accurately adjusted.
That is, the white balance coefficient cannot be accurately set if it is determined from image sensing data in order to obtain an optimum reproduced image.
Also, in the setting of the reproduction luminance level, if the reproduction luminance level (range) is determined for each image plane, the correlation between the luminances of a plurality of image planes is lost. This makes the comparison of reproduced images difficult, or the connection of luminances becomes unnatural when the reproduced images are synthesized.
For example, the above inconveniences are significant when an object which is to be originally, desirably photographed as one image plane is divisionally photographed because the photographing area is small and one image plane is formed by synthesizing image sensing data of the obtained image planes.
That is, in the method of obtaining an image production parameter for each image sensing data of one image plane, it is impossible to obtain a reproduced image which is used when information between a plurality of images is extracted by comparing and analyzing the images, such as when physical property information is obtained from luminance information. Also, if the reflectance of an object spatially, gradually changes, individual image sensing data obtained by divisionally photographing the object have different luminance levels (ranges). If images are reproduced by independently optimizing these image sensing data, the correlation between luminances originally corresponding to the respective image sensing areas is lost in the reproduced images. Accordingly, if one image is formed by synthesizing these images taken in the respective image sensing areas, an unnatural synthetic image in which the correlation between luminances is lost results.
The hue of an image is adjusted by adjusting the white balance as follows. An object which is supposed to look white under a certain photographing light source is photographed. The amplification factor of each of a plurality of color component signals constituting an image signal obtained from the image sensing device is so adjusted that the white object accurately looks white when the image signal is reproduced. That is, it can be considered that the white balance adjustment is performed to compensate for changes in the light source during photography.
Commonly, the white balance adjustment described above is a principal means for compensating for changes in the light source during photography. A white balance coefficient used in this white balance adjustment is obtained on the basis of information of the light source during photography.
Of a plurality of different image reproduction parameters used in image reproduction, some parameters are preferably obtained on the basis of information of the light source during photography, like the image reproduction parameter (white balance coefficient) used in the white balance adjustment. An example is a complementary color-pure color conversion matrix used to convert an image signal obtained by using a complementary color filter into a pure color signal.
The complementary color-pure color conversion matrix is determined by the spectral transmittance characteristic of a complementary color filter. Usually, the spectral transmittance characteristic of a complementary color filter is not ideal. The influence of this difference from the ideal characteristic changes in accordance with the characteristics of the light source during photography. That is, a complementary color-pure color conversion matrix optimally selected under a certain photographing light source gives an optimum complementary color-pure color conversion result under this light source. However, this matrix does not give suitable conversion results to all light sources.
When a photographing light source changes, therefore, it is desirable to change the complementary color-pure color conversion matrix in accordance with the light source. Also, the above two image reproduction parameters, i.e., the white balance coefficient and the complementary color-pure color conversion matrix, are related to each other under a certain photographing light source. Accordingly, it is undesirable to individually determine these parameters.
Generally, however, the complementary color-pure color conversion is performed by using a semi-fixed complementary color-pure color conversion matrix which is optimally set under a certain photographing light source. If the photographing light source changes, therefore, the influence of the difference of the spectral transmittance characteristic of a complementary color filter from the ideal characteristic increases. Also, a contradiction sometimes occurs between the white balance coefficient and the complementary color-pure color conversion matrix having the correlation. Consequently, no complementary color-pure color conversion can be properly performed, and this makes faithful reproduction of an image difficult.